Publications by authors named "Deborah J Thompson"

70 Publications

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 Aug 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
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http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
August 2021

Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers.

Cancer Epidemiol Biomarkers Prev 2021 01 3;30(1):217-228. Epub 2020 Nov 3.

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.

Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.

Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers ( = 0.43, = 2.66 × 10). We found seven loci associated with risk for both cancers ( < 2.4 × 10). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified ( < 5 × 10). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.

Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.

Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-0739DOI Listing
January 2021

Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer.

Int J Cancer 2021 01 7;148(2):307-319. Epub 2020 Aug 7.

Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia, USA.

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.
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http://dx.doi.org/10.1002/ijc.33206DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7757859PMC
January 2021

Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers.

Nat Commun 2020 07 3;11(1):3353. Epub 2020 Jul 3.

Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.
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http://dx.doi.org/10.1038/s41467-020-16483-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335068PMC
July 2020

Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan.

Nat Commun 2020 03 24;11(1):1536. Epub 2020 Mar 24.

MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus Box 285, Cambridge, CB2 0QQ, UK.

The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.
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http://dx.doi.org/10.1038/s41467-020-14451-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093467PMC
March 2020

External Validation of Risk Prediction Models Incorporating Common Genetic Variants for Incident Colorectal Cancer Using UK Biobank.

Cancer Prev Res (Phila) 2020 06 18;13(6):509-520. Epub 2020 Feb 18.

The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

The aim of this study was to compare and externally validate risk scores developed to predict incident colorectal cancer that include common genetic variants (SNPs), with or without established lifestyle/environmental (questionnaire-based/classical/phenotypic) risk factors. We externally validated 23 risk models from a previous systematic review in 443,888 participants ages 37 to 73 from the UK Biobank cohort who had 6-year prospective follow-up, no prior history of colorectal cancer, and data for incidence of colorectal cancer through linkage to national cancer registries. There were 2,679 (0.6%) cases of incident colorectal cancer. We assessed model discrimination using the area under the operating characteristic curve (AUC) and relative risk calibration. The AUC of models including only SNPs increased with the number of included SNPs and was similar in men and women: the model by Huyghe with 120 SNPs had the highest AUC of 0.62 [95% confidence interval (CI), 0.59-0.64] in women and 0.64 (95% CI, 0.61-0.66) in men. Adding phenotypic risk factors without age improved discrimination in men but not in women. Adding phenotypic risk factors and age increased discrimination in all cases ( < 0.05), with the best performing models including SNPs, phenotypic risk factors, and age having AUCs between 0.64 and 0.67 in women and 0.67 and 0.71 in men. Relative risk calibration varied substantially across the models. Among middle-aged people in the UK, existing polygenic risk scores discriminate moderately well between those who do and do not develop colorectal cancer over 6 years. Consideration should be given to exploring the feasibility of incorporating genetic and lifestyle/environmental information in any future stratified colorectal cancer screening program.
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http://dx.doi.org/10.1158/1940-6207.CAPR-19-0521DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610623PMC
June 2020

Association between genetic polymorphisms and endometrial cancer risk: a systematic review.

J Med Genet 2020 09 17;57(9):591-600. Epub 2020 Feb 17.

Division of Cancer Sciences, University of Manchester, Manchester, UK

Introduction: Endometrial cancer is one of the most commonly diagnosed cancers in women. Although there is a hereditary component to endometrial cancer, most cases are thought to be sporadic and lifestyle related. The aim of this study was to systematically review prospective and retrospective case-control studies, meta-analyses and genome-wide association studies to identify genomic variants that may be associated with endometrial cancer risk.

Methods: We searched MEDLINE, Embase and CINAHL from 2007 to 2019 without restrictions. We followed PRISMA 2009 guidelines. The search yielded 3015 hits in total. Following duplicate exclusion, 2674 abstracts were screened and 453 full-texts evaluated based on our pre-defined screening criteria. 149 articles were eligible for inclusion.

Results: We found that single nucleotide polymorphisms (SNPs) in , , , , and were strongly associated with incident endometrial cancer. Nineteen variants were reported with genome-wide significance and a further five with suggestive significance. No convincing evidence was found for the widely studied variant rs2279744. Publication bias and false discovery rates were noted throughout the literature.

Conclusion: Endometrial cancer risk may be influenced by SNPs in genes involved in cell survival, oestrogen metabolism and transcriptional control. Larger cohorts are needed to identify more variants with genome-wide significance.
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http://dx.doi.org/10.1136/jmedgenet-2019-106529DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476276PMC
September 2020

Using human genetics to understand the disease impacts of testosterone in men and women.

Nat Med 2020 02 10;26(2):252-258. Epub 2020 Feb 10.

Medical Research Council (MRC) Epidemiology Unit, University of Cambridge, Cambridge, UK.

Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22-1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33-1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76-0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses.
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http://dx.doi.org/10.1038/s41591-020-0751-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025895PMC
February 2020

Genetic predisposition to mosaic Y chromosome loss in blood.

Nature 2019 11 20;575(7784):652-657. Epub 2019 Nov 20.

Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.
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http://dx.doi.org/10.1038/s41586-019-1765-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6887549PMC
November 2019

Impact of a Central-Line Insertion Site Assessment (CLISA) score on localized insertion site infection to prevent central-line-associated bloodstream infection (CLABSI).

Infect Control Hosp Epidemiol 2020 01 8;41(1):59-66. Epub 2019 Nov 8.

Epidemiology & Infection Prevention Program, University of California, Irvine Health, Orange, California.

Objective: To assess the impact of a newly developed Central-Line Insertion Site Assessment (CLISA) score on the incidence of local inflammation or infection for CLABSI prevention.

Design: A pre- and postintervention, quasi-experimental quality improvement study.

Setting And Participants: Adult inpatients with central venous catheters (CVCs) hospitalized in an intensive care unit or oncology ward at a large academic medical center.

Methods: We evaluated CLISA score impact on insertion site inflammation and infection (CLISA score of 2 or 3) incidence in the baseline period (June 2014-January 2015) and the intervention period (April 2015-October 2017) using interrupted times series and generalized linear mixed-effects multivariable analyses. These were run separately for days-to-line removal from identification of a CLISA score of 2 or 3. CLISA score interrater reliability and photo quiz results were evaluated.

Results: Among 6,957 CVCs assessed 40,846 times, percentage of lines with CLISA score of 2 or 3 in the baseline and intervention periods decreased by 78.2% (from 22.0% to 4.7%), with a significant immediate decrease in the time-series analysis (P < .001). According to the multivariable regression, the intervention was associated with lower percentage of lines with a CLISA score of 2 or 3, after adjusting for age, gender, CVC body location, and hospital unit (odds ratio, 0.15; 95% confidence interval, 0.06-0.34; P < .001). According to the multivariate regression, days to removal of lines with CLISA score of 2 or 3 was 3.19 days faster after the intervention (P < .001). Also, line dwell time decreased 37.1% from a mean of 14 days (standard deviation [SD], 10.6) to 8.8 days (SD, 9.0) (P < .001). Device utilization ratios decreased 9% from 0.64 (SD, 0.08) to 0.58 (SD, 0.06) (P = .039).

Conclusions: The CLISA score creates a common language for assessing line infection risk and successfully promotes high compliance with best practices in timely line removal.
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http://dx.doi.org/10.1017/ice.2019.291DOI Listing
January 2020

Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review.

Cancer Epidemiol Biomarkers Prev 2019 10 10;28(10):1580-1593. Epub 2019 Jul 10.

The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs.
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http://dx.doi.org/10.1158/1055-9965.EPI-19-0059DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610631PMC
October 2019

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk.

Breast Cancer Res 2019 05 22;21(1):68. Epub 2019 May 22.

Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.

Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.

Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.

Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.

Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
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http://dx.doi.org/10.1186/s13058-019-1138-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532188PMC
May 2019

Genome-Wide Association Studies of Endometrial Cancer: Latest Developments and Future Directions.

Cancer Epidemiol Biomarkers Prev 2019 07 30;28(7):1095-1102. Epub 2019 Apr 30.

Molecular Cancer Epidemiology Group, Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Endometrial cancer, the most commonly diagnosed cancer of the female reproductive tract in developed countries, has a heritable component. To date, 16 genetic risk regions have been robustly discovered by genome-wide association studies (GWAS) of endometrial cancer. Post-GWAS analyses including expression quantitative trait loci analysis and laboratory-based functional studies have been successful in identifying genes and pathways involved in endometrial carcinogenesis. Mendelian randomization analysis studies have confirmed factors causal for endometrial cancer risk, including increased body mass index and early onset of menarche. In this review, we summarize findings from GWAS and post-GWAS analyses of endometrial cancer. We discuss clinical implications of these findings, current knowledge gaps, and future directions for the study of endometrial cancer genetics.
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http://dx.doi.org/10.1158/1055-9965.EPI-18-1031DOI Listing
July 2019

Assessing the Role of Selenium in Endometrial Cancer Risk: A Mendelian Randomization Study.

Front Oncol 2019 27;9:182. Epub 2019 Mar 27.

Molecular Cancer Epidemiology Group, Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

Endometrial cancer is the most commonly diagnosed gynecological cancer in developed countries. Based on evidence from observational studies which suggest selenium inhibits the development of several cancers (including lung and prostate cancer), selenium supplementation has been touted as a potential cancer preventative agent. However, randomized controlled trials have not reported benefit for selenium supplementation in reducing cancer risk. For endometrial cancer, limited observational studies have been conducted assessing whether selenium intake, or blood selenium levels, associated with reduced risk, and no randomized controlled trials have been conducted. We performed a two-sample Mendelian randomization analysis to examine the relationship between selenium levels (using a composite measure of blood and toenail selenium) and endometrial cancer risk, using summary statistics for four genetic variants associated with selenium levels at genome-wide significance levels ( < 5 × 10), from a study of 12,906 endometrial cancer cases and 108,979 controls, all of European ancestry. Inverse variance weighted (IVW) analysis indicated no evidence of a causal role for selenium levels in endometrial cancer development (OR per unit increase in selenium levels Z-score = 0.99, 95% CI = 0.87-1.14). Similar results were observed for sensitivity analyses robust to the presence of unknown pleiotropy (OR per unit increase in selenium levels Z-score = 0.98, 95% CI 0.89-1.08 for weighted median; OR per unit increase in selenium levels Z-score = 0.90, 95% CI = 0.53-1.50 for MR-Egger). In conclusion, these results do not support the use of selenium supplementation to prevent endometrial cancer.
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http://dx.doi.org/10.3389/fonc.2019.00182DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445879PMC
March 2019

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Nat Genet 2019 03 18;51(3):452-469. Epub 2019 Feb 18.

Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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http://dx.doi.org/10.1038/s41588-018-0334-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560635PMC
March 2019

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci.

Mol Psychiatry 2020 10 7;25(10):2392-2409. Epub 2019 Jan 7.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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http://dx.doi.org/10.1038/s41380-018-0313-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515840PMC
October 2020

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Am J Hum Genet 2019 01 13;104(1):21-34. Epub 2018 Dec 13.

Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland; Department of Oncology, Örebro University Hospital, Örebro 70185, Sweden.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
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http://dx.doi.org/10.1016/j.ajhg.2018.11.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323553PMC
January 2019

Identification of nine new susceptibility loci for endometrial cancer.

Nat Commun 2018 08 9;9(1):3166. Epub 2018 Aug 9.

Department of Obstetrics and Gynecology, University Hospitals KU Leuven, University of Leuven, Division of Gynecologic Oncology, Leuven, 3000, Belgium.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.
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http://dx.doi.org/10.1038/s41467-018-05427-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6085317PMC
August 2018

Genetic predictors of testosterone and their associations with cardiovascular disease and risk factors: A Mendelian randomization investigation.

Int J Cardiol 2018 Sep 18;267:171-176. Epub 2018 May 18.

Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge, Cambridgeshire, UK; Homerton College, University of Cambridge, Cambridge, Cambridgeshire, UK. Electronic address:

Background: Testosterone supplementation has been linked to increased cardiovascular disease risk in some observational studies. The causal role of testosterone can be investigated using a Mendelian randomization approach.

Methods And Results: We assessed genetic associations of variants in two gene regions (SHBG and JMJD1C) with several cardiovascular risk factors (lipids, adiponectin, blood pressure, anthropometric traits) plus male pattern baldness, including control outcomes and potential mediators. We assessed genetic associations with coronary artery disease (CAD) risk in the CARDIoGRAMplusC4D consortium (171,191 individuals including 60,801 cases), and associations with CAD and ischaemic stroke risk in the UK Biobank (367,643 individuals including 25,352 CAD cases and 3650 ischaemic stroke cases). Genetic predictors of increased serum testosterone were associated with lipids, blood pressure, and height. There was some evidence of an association with risk of CAD (SHBG gene region: odds ratio (OR) 0.95 per 1 unit increase in log-transformed testosterone [95% confidence interval: 0.81-1.12, p = 0.55]; JMJD1C gene region: OR 1.24 [1.01-1.51, p = 0.04]) and ischaemic stroke both overall (SHBG: OR 1.05 [0.64, 1.73, p = 0.83]; JMJD1C: OR 2.52 [1.33, 4.77, p = 0.005]) and in men. However, associations with some control outcomes were in the opposite direction to that expected.

Conclusions: Sex hormone-related mechanisms appear to be relevant to cardiovascular risk factors and for stroke (particularly for men). However, the extent that these findings are specifically informative about endogenous testosterone or testosterone supplementation is unclear. These findings underline a fundamental limitation for the use of Mendelian randomization where biological knowledge about the function of genetic variants is uncertain.
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http://dx.doi.org/10.1016/j.ijcard.2018.05.051DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024225PMC
September 2018

Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses.

Cancer Med 2018 05 2;7(5):1978-1987. Epub 2018 Apr 2.

Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium.

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (r = 0.23, P = 9.3 × 10 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10 ) and concordance in effect direction (P = 2.0 × 10 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.
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http://dx.doi.org/10.1002/cam4.1445DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5943470PMC
May 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Exome array analysis identifies GPR35 as a novel susceptibility gene for anthracycline-induced cardiotoxicity in childhood cancer.

Pharmacogenet Genomics 2017 Dec;27(12):445-453

aHuman Genotyping Unit-CeGen bHuman Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO) cPediatric Solid Tumor Laboratory, Human Genetic Department, Research Institute of Rare Diseases, Instituto de Salud Carlos III dDepartment of Pediatric Hemato-Oncology eDepartment of Pediatric Cardiology, Hospital Universitario La Paz fDepartment of Pediatrics, Hospital Universitario Infanta Elena, Madrid gDepartment of Pediatrics, University Clinic of Navarra, Universidad de Navarra, Pamplona, Spain hDepartment of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology iDepartment of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK jDepartment of Electron Microscopy/Molecular Pathology, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.

Objectives: Pediatric cancer survivors are a steadily growing population; however, chronic anthracycline-induced cardiotoxicity (AIC) is a serious long-term complication leading to considerable morbidity. We aimed to identify new genes and low-frequency variants influencing the susceptibility to AIC for pediatric cancer patients.

Patients And Methods: We studied the association of variants on the Illumina HumanExome BeadChip array in 83 anthracycline-treated pediatric cancer patients. In addition to single-variant association tests, we carried out a gene-based analysis to investigate the combined effects of common and low-frequency variants to chronic AIC.

Results: Although no single-variant showed an association with chronic AIC that was statistically significant after correction for multiple testing, we identified a novel significant association for G protein-coupled receptor 35 (GPR35) by gene-based testing, a gene with potential roles in cardiac physiology and pathology (P=7.0×10), which remained statistically significant after correction for multiple testing (PFDR=0.03). The greatest contribution to this observed association was made by rs12468485, a missense variant (p.Thr253Met, c.758C>T, minor allele frequency=0.04), with the T allele associated with an increased risk of chronic AIC and more severe symptomatic cardiac manifestations at low anthracycline doses.

Conclusion: Using exome array data, we identified GPR35 as a novel susceptibility gene associated with chronic AIC in pediatric cancer patients.
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http://dx.doi.org/10.1097/FPC.0000000000000309DOI Listing
December 2017

Dissecting Causal Pathways Using Mendelian Randomization with Summarized Genetic Data: Application to Age at Menarche and Risk of Breast Cancer.

Genetics 2017 10 23;207(2):481-487. Epub 2017 Aug 23.

MRC Epidemiology Unit, University of Cambridge, CB2 0QQ Cambridgeshire, United Kingdom.

Mendelian randomization is the use of genetic variants as instrumental variables to estimate causal effects of risk factors on outcomes. The total causal effect of a risk factor is the change in the outcome resulting from intervening on the risk factor. This total causal effect may potentially encompass multiple mediating mechanisms. For a proposed mediator, the direct effect of the risk factor is the change in the outcome resulting from a change in the risk factor, keeping the mediator constant. A difference between the total effect and the direct effect indicates that the causal pathway from the risk factor to the outcome acts at least in part via the mediator (an indirect effect). Here, we show that Mendelian randomization estimates of total and direct effects can be obtained using summarized data on genetic associations with the risk factor, mediator, and outcome, potentially from different data sources. We perform simulations to test the validity of this approach when there is unmeasured confounding and/or bidirectional effects between the risk factor and mediator. We illustrate this method using the relationship between age at menarche and risk of breast cancer, with body mass index (BMI) as a potential mediator. We show an inverse direct causal effect of age at menarche on risk of breast cancer (independent of BMI), and a positive indirect effect via BMI. In conclusion, multivariable Mendelian randomization using summarized genetic data provides a rapid and accessible analytic strategy that can be undertaken using publicly available data to better understand causal mechanisms.
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http://dx.doi.org/10.1534/genetics.117.300191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629317PMC
October 2017

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Nat Genet 2017 Jun 24;49(6):834-841. Epub 2017 Apr 24.

Institute of Genetics and Biophysics, CNR, Naples, Italy.

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
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http://dx.doi.org/10.1038/ng.3841DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841952PMC
June 2017

Genetic variants associated with mosaic Y chromosome loss highlight cell cycle genes and overlap with cancer susceptibility.

Nat Genet 2017 May 27;49(5):674-679. Epub 2017 Mar 27.

MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.

The Y chromosome is frequently lost in hematopoietic cells, which represents the most common somatic alteration in men. However, the mechanisms that regulate mosaic loss of chromosome Y (mLOY), and its clinical relevance, are unknown. We used genotype-array-intensity data and sequence reads from 85,542 men to identify 19 genomic regions (P < 5 × 10) that are associated with mLOY. Cumulatively, these loci also predicted X chromosome loss in women (n = 96,123; P = 4 × 10). Additional epigenome-wide methylation analyses using whole blood highlighted 36 differentially methylated sites associated with mLOY. The genes identified converge on aspects of cell proliferation and cell cycle regulation, including DNA synthesis (NPAT), DNA damage response (ATM), mitosis (PMF1, CENPN and MAD1L1) and apoptosis (TP53). We highlight the shared genetic architecture between mLOY and cancer susceptibility, in addition to inferring a causal effect of smoking on mLOY. Collectively, our results demonstrate that genotype-array-intensity data enables a measure of cell cycle efficiency at population scale and identifies genes implicated in aneuploidy, genome instability and cancer susceptibility.
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http://dx.doi.org/10.1038/ng.3821DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5973269PMC
May 2017

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study.

JAMA Oncol 2017 May;3(5):636-651

Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire.

Importance: The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

Objective: To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

Data Sources: Genomewide association studies (GWAS) published up to January 15, 2015.

Study Selection: GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

Data Extraction And Synthesis: Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

Main Outcomes And Measures: Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

Results: Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

Conclusions And Relevance: It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.
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http://dx.doi.org/10.1001/jamaoncol.2016.5945DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638008PMC
May 2017

Rare and low-frequency coding variants alter human adult height.

Nature 2017 02 1;542(7640):186-190. Epub 2017 Feb 1.

Netherlands Comprehensive Cancer Organisation, Utrecht, 3501 DB, The Netherlands.

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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http://dx.doi.org/10.1038/nature21039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302847PMC
February 2017
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